AI stack · Agentic systems
Agents that plan, call tools, and stop.
Agentforce when the work lives in Salesforce. A code agent or SDK when it does not. MCP and A2A so the pieces talk without a custom API each time. The first week is in the org, reading what already exists.
Certified Partner since 2010 · MVP Hall of Fame · 200+ agents in production · UAE and US desks
- 01Models · Claude, Gemini, OpenAI, Bedrock
- 02Agents · Agentforce, CrewAI, ADK, A2A
- 03Memory · Neo4j, Cognee, RAG
- 04Identity · IndyKite, SSO, entitlements
- 05Governance · policy, audit, human override
On this layer
What we put in.
The honest no: if the work is a software factory with a named delivery date, we are the wrong partner.
Google ADK
Google Agent Development Kit on Vertex AI.
A2A Protocol
Agent2Agent interop across CrewAI, ADK, and Agentforce.
Claude Agent SDK
Multi-turn Claude agents that validate output before writing.
OpenAI Agents SDK
Typed agent steps: structured outputs and function calling.
LangGraph
Cyclic agent graphs with human approval gates.
Agentforce
Salesforce-native agents. Use when the work lives in the org.
CrewAI
Multi-agent automation that replaces brittle RPA scripts.
MuleSoft Agent Fabric
Orchestrate AI agents across your Salesforce ecosystem.
Model Context Protocol
Standard tool and data connectors for AI agents.
Where it shows up
The work this layer does.
Use cases where these tools carry the job. Each one names the stack.
AI IT Support Transformation
Ticket triage and knowledge agents on Vertex.
Quality assurance
Specialist agents for test design and defect clustering.
Data analytics
Agents that query governed datasets, not a raw warehouse dump.
Product development
Research and spec agents that stay inside Google Cloud.
AI Customer Service Transformation
Voice, chat, and CRM agents handing off without a custom API each time.
Supply chain
Planning agents that call finance or inventory specialists.
Compliance monitoring
A record of which agent called which agent, and why.
Legal document review
Contract and clause work the org-native agent should refuse.
Contract management
Lifecycle review with citations a reviewer can open.
Questions
What buyers ask us.
- Agentforce or a custom agent?
- Agentforce when the records, the permissions and the people already live in Salesforce. A custom agent on an SDK when the seat is Slack, WhatsApp or another system. Many programs run both, with a control plane in front.
- Do we need MCP or A2A?
- MCP when an agent needs governed access to tools and data. A2A when agents from different vendors must hand work to each other. Neither is required for a first agent on one process.
- How do you stop an agent doing something wrong?
- Limits on steps and tools, an identity that inherits the user permissions, and a person on any write that commits the firm. Every run is logged so a reviewer can see why it acted.
The rest of the stack
One layer is not a system.
The plane this layer lives in, and the other four layers.
Runtime plane
Classify the step first. The framework is a consequence.
Models
The reasoning layer. We pick the model that fits the job, then deploy it so data stays where it should.
Agentic memory
What the agent remembers: graphs, identity, and long-term context so answers stay grounded.
Automation and voice
Workflows and voice agents that connect models to Salesforce and the rest of the stack.
How we engage
Deployment and governance. The work that turns a pilot into a production system.
Before you pick a partner
Read these first. Then call anyone.
Our buyer guides. They apply whether or not you hire us.
Choosing an AI partner in the UAE
Five kinds of partner compared, the PDPL, DIFC, Arabic and WhatsApp questions, and red flags.
Choosing an AI implementation partner
Evaluation criteria, deployment models, governance fluency, and red flags.
AI partner evaluation framework
A five-part scorecard: depth, governance, integration, security, delivery.
Questions to ask an AI partner
Architecture, security, governance, pricing, and who is accountable.
AI partner vs in-house team
Hiring timelines, real costs, and dependency risk, scenario by scenario.
AI pilot to production
Which of the four ways your pilot stalled, and the sequence that moves it.
The brief
Send the situation.
Name the process. We tell you which layer is missing.